Published March 1, 2026 | Version 0.4.0
Software Open

SCPN Control: Neuro-Symbolic Stochastic Petri Net Controller for Plasma Control

Authors/Creators

  • 1. ANULUM CH & LI

Description

Standalone neuro-symbolic control engine that compiles Stochastic Petri Nets into spiking neural network controllers with formal verification guarantees. Features real-time adaptive Kuramoto coupling driven by tokamak diagnostics (beta, disruption risk, Mirnov, coherence PI), Lyapunov stability guard, H-infinity observer, plasma-native 8-layer Knm hierarchy, and WebSocket phase streaming. 52 Python modules, 5 Rust crates, 1888 tests.

Notes

Part of the SCPN (Self-Consistent Phenomenological Network) research framework by ANULUM. v0.4.0 introduces real-time adaptive Knm coupling driven by tokamak diagnostics — the first Kuramoto phase dynamics engine with online-adaptive coupling from plasma state.

Files

scpn-control-0.4.0.zip

Files (10.3 MB)

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Additional details

Identifiers

URL
https://pypi.org/project/scpn-control/

Related works

Is documented by
https://anulum.github.io/scpn-control (URL)
Is supplement to
https://github.com/anulum/scpn-control (URL)
arXiv:2004.06344 (arXiv)
References
https://github.com/anulum/scpn-fusion-core (URL)
https://github.com/anulum/scpn-quantum-control (URL)